Search results
21 – 30 of over 13000Mahmoud Awad, Malick Ndiaye and Ahmed Osman
Cold supply chain (CSC) distribution systems are vital in preserving the integrity and freshness of transported temperature sensitive products. CSC is also known to be energy…
Abstract
Purpose
Cold supply chain (CSC) distribution systems are vital in preserving the integrity and freshness of transported temperature sensitive products. CSC is also known to be energy intensive with a significant emission footprint. As a result, CSC requires strict monitoring and control management system during storage and transportation to improve safety and reduce profit losses. In this research, a systematic review of recent literature related to the distribution of food CSC products is presented and possible areas to extend research in modeling and decision-making are identified.
Design/methodology/approach
The paper analyzes the content of 65 recent articles related to CSC and perishable foods. Several relevant keywords were used in the initial search, which generated a list of 214 articles. The articles were screened based on content relevance in terms of food vehicle routing modeling and quality. Selected articles were categorized and analyzed based on cost elements, modeling framework and solution approach. Finally, recommendations for future research are suggested.
Findings
The review identified several research gaps in CSC logistics literature, where more focused research is warranted. First, the review suggests that dynamic vehicle modeling and routing while considering products quality and environmental impacts is still an open area for research. Second, there is no consensus among researchers in terms of quality degradation models used to assess the freshness of transported cold food. As a result, an investigation of critical parameters and quality modeling is warranted. Third, and due to the problem complexity, there is a need for developing heuristics and metaheuristics to solve such models. Finally, there is a need for extending the single product single compartment CSC to multi-compartment multi-temperature routing modeling.
Originality/value
The article identified possible areas to extend research in CSC distribution modeling and decision-making. Modified models that reflect real applications will help practitioners, food authorities and researchers make timely and more accurate decisions that will reduce food waste and improve the freshness of transported food.
Details
Keywords
Ronghua Cai, Jiamei Yang, Xuemin Xu and Aiping Jiang
The purpose of this paper is to propose an improved multi-objective optimization model for the condition-based maintenance (CBM) of single-component systems which considers…
Abstract
Purpose
The purpose of this paper is to propose an improved multi-objective optimization model for the condition-based maintenance (CBM) of single-component systems which considers periodic imperfect maintenance and ecological factors.
Design/methodology/approach
Based on the application of non-periodic preventive CBM, two recursion models are built for the system: hazard rate and the environmental degradation factor. This paper also established an optimal multi-objective model with a normalization process. The multiple-attribute value theory is used to obtain the optimal preventive maintenance (PM) interval. The simulation and sensitivity analyses are applied to obtain further rules.
Findings
An increase in the number of the occurrences could shorten the duration of a maintenance cycle. The maintenance techniques and maintenance efficiency could be improved by increasing system availability, reducing cost rate and improving degraded condition.
Practical implications
In reality, a variety of environmental situations may occur subsequent to the operations of an advanced manufacturing system. This model could be applied in real cases to help the manufacturers better discover the optimal maintenance cycle with minimized cost and degraded condition of the environment, helping the corporations better fulfill their CSR as well.
Originality/value
Previous research on single-component condition-based predictive maintenance usually focused on the maintenance costs and availability of a system, while ignoring the possible pollution from system operations. This paper proposed a modified multi-objective optimization model considering environment influence which could more comprehensively analyze the factors affecting PM interval.
Details
Keywords
The purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance…
Abstract
Purpose
The purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance effectiveness.
Design/methodology/approach
The PdM system updates the degradation model using partial condition monitoring information based on degradation type judgment. In addition, an extended multi-step-ahead updating stopping condition is adopted for performance enhancement of the PdM system.
Findings
An extensive numerical investigation compares the performance of the PdM system with the corresponding preventive maintenance (PM) policy. By carefully choosing the updating stopping condition, the PdM policy performs better than the corresponding PM policy.
Research limitations/implications
The proposed PdM system is applicable to single-unit systems. And the continuous degradation process should be well modeled by the stochastic linear degradation model (Gebraeel et al., 2009).
Originality/value
In literature, there are abundant studies on PdM policies for continuous degradation processes. However, research on hybrid degradation processes still focuses on condition-based maintenance policy and a PdM policy for a hybrid degradation process is still unreported. In this paper, a PdM system for hybrid degradation processes with continuous degradation and sudden damage is proposed. The PdM system decides PM schedules by fully utilizing the condition monitoring data of each specific product, and can hopefully improve maintenance effectiveness.
Details
Keywords
Hadef Hefaidh, Djebabra Mébarek, Negrou Belkhir and Zied Driss
The reliability prediction is among the most important objectives for achieving overall system performance, and this prediction carried out by anticipating system performance…
Abstract
Purpose
The reliability prediction is among the most important objectives for achieving overall system performance, and this prediction carried out by anticipating system performance degradation. In this context, the purpose of this research paper is to development of methodology for the photovoltaic (PV) modules' reliability prediction taking into account their future operating context.
Design/methodology/approach
The proposed methodology is framed by dependability methods, in this regard, two methods of dysfunctional analysis were used, the Failure Mode and Effects Criticality Analysis (FMECA) method is carried out for identification of the degradation modes, and the Fault Tree Analysis (FTA) method is used for identification the causes of PV modules degradation and the parameters influencing its degradation. Then, based on these parameters, accelerated tests have been used to predict the reliability of PV modules.
Findings
The application of the proposed methodology on PWX 500 PV modules' in different regions of Algeria makes it possible to predict its reliability, taking into account the future constraints on its operation. In this case, the temperature and relative humidity vary from one region to another was chosen as constraints. The results obtained from the different regions confirms the reliability provided by the designer of the Saharan cities Biskra, In Salah, Tamanraset, and affirms this value for the two Mediterranean cities of Oran and Algiers.
Originality/value
The proposed methodology is developed for the reliability prediction of the PV modules taking into account their future operating context and, the choice of different regions confirms or disproves the reliability provided by the designer of the PV modules studied. This application confirms their performance within the framework of the reliability prediction.
Details
Keywords
JiangYou Yu, Le Cao, Hao Fu and Jun Guo
Stencil cleaning is an important operation in solder paste printing process. Frequent cleaning may interrupt printing process and increase idle time, as well as loss for…
Abstract
Purpose
Stencil cleaning is an important operation in solder paste printing process. Frequent cleaning may interrupt printing process and increase idle time, as well as loss for performing cleaning. This paper aims to propose a method to optimize the stencil cleaning time and reduce unnecessary cleaning operations and losses.
Design/methodology/approach
This paper uses a discrete-time, discrete-state homogeneous Markov chain to model the stencil printing performance degradation process, and the quality loss during the stencil printing process is estimated based on this degradation model. A stencil cleaning decision model based on renewal reward theorem is established, and the optimal cleaning time is obtained through a balance between quality loss and the loss on idle time.
Findings
A stencil cleaning decision model for solder paste printing is established, and numerical simulation results show that there exists an optimal stencil cleaning time which minimizes the long-term loss.
Originality/value
Stencil cleaning control is very important for solder paste printing. However, there are very few studies focusing on stencil cleaning control. This research contributes to developing a model to optimize the stencil cleaning time in solder paste printing process.
Details
Keywords
Jie Lin and Minghua Wei
With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply (UPS), the prediction of remaining useful life (RUL) for…
Abstract
Purpose
With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply (UPS), the prediction of remaining useful life (RUL) for lithium-ion battery played an important role. More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL. The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.
Design/methodology/approach
In this paper, a simple and effective RUL prediction method based on the combination method of auto-regression (AR) time-series model and particle filter (PF) was proposed for lithium-ion battery. The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training. By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations, the proposed PF + AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.
Findings
Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR + PF algorithm both on original exponential empirical degradation model and the deformed double-exponential one. Experimental results have shown that the proposed PF + AR method improved the prediction accuracy, decreases the error rate and reduces the uncertainty ranges of RUL, which was more suitable for the deformed double-exponential empirical degradation model.
Originality/value
In the running of UPS device based on lithium-ion battery, the proposed AR + PF combination algorithm will quickly, accurately and robustly predict the RUL of lithium-ion batteries, which had a strong application value in the stable operation of laboratory and other application scenarios.
Details
Keywords
Yasin Özcelep and Ayten Kuntman
The purpose of this paper is to propose a time‐dependent mobility degradation model which is independent from the process or operating conditions.
Abstract
Purpose
The purpose of this paper is to propose a time‐dependent mobility degradation model which is independent from the process or operating conditions.
Design/methodology/approach
In total, four transistors under test are electrically stressed using constant positive electrical stress voltage technique with the gate bias of VG=40 V DC, where the source and drain were grounded. The authors increased the stress voltage step by step to avoid electrostatic discharge and recorded the ID‐VDS and ID‐VGS measurements in time intervals during the stress.
Findings
The experimental results show that the output current and the threshold voltage of the transistor are increased after the stress. Mobility and channel length are decreased. The changes in the transistor parameters were associated to interface state Si/SiO2 effects. The authors used the physical changes in transistor and proposed a new‐time dependent mobility degradation model. The mobility change was calculated using the proposed model and compared with the experimental results. It was seen that the calculated and experimental results are in good agreement.
Originality/value
This is an original research paper and enables the mobility degradation to be predicted independently from effects of process or operational changes such as oxide thickness, substrate doping, and applied voltages on transistor.
Details
Keywords
Afef Saihi, Mohamed Ben-Daya and Rami Afif As'ad
Maintenance is a critical business function with a great impact on economic, environmental and social aspects. However, maintenance decisions' planning has been driven by merely…
Abstract
Purpose
Maintenance is a critical business function with a great impact on economic, environmental and social aspects. However, maintenance decisions' planning has been driven by merely economic and technical measures with inadequate consideration of environmental and social dimensions. This paper presents a review of the literature pertaining to sustainable maintenance decision-making models supported by a bibliometric analysis that seeks to establish the evolution of this research over time and identify the main research clusters.
Design/methodology/approach
A systematic literature review, supported with a bibliometric and network analysis, of the extant studies is conducted. The relevant literature is categorized based on which sustainability pillar, or possibly multiple ones, is being considered with further classification outlining the application area, modeling approach and the specific peculiarities characterizing each area.
Findings
The review revealed that maintenance and sustainability modeling is an emerging area of research that has intensified in the last few years. This fertile area can be developed further in several directions. In particular, there is room for devising models that are implementable, based on reliable and timely data with proven tangible practical results. While the environmental aspect has been considered, there is a clear scarcity of works addressing the social dimension. One of the identified barriers to developing applicable models is the lack of the required, accurate and timely data.
Originality/value
This work contributes to the maintenance and sustainability modeling research area, provides insights not previously addressed and highlights several avenues for future research. To the best of the authors' knowledge, this is the first review that looks at the integration of sustainability issues in maintenance modeling and optimization.
Details
Keywords
Vinod Nistane and Suraj Harsha
In rotary machines, the bearing failure is one of the major causes of the breakdown of machinery. The bearing degradation monitoring is a great anxiety for the prevention of…
Abstract
Purpose
In rotary machines, the bearing failure is one of the major causes of the breakdown of machinery. The bearing degradation monitoring is a great anxiety for the prevention of bearing failures. This paper aims to present a combination of the stationary wavelet decomposition and extra-trees regression (ETR) for the evaluation of bearing degradation.
Design/methodology/approach
The higher order cumulants features are extracted from the bearing vibration signals by using the stationary wavelet decomposition (stationary wavelet transform [SWT]). The extracted features are then subjected to the ETR for obtaining normal and failure state. A dominance level curve build using the dissimilarity data of test object and retained as health degradation indicator for the evaluation of bearing health.
Findings
Experiment conducts to verify and assess the effectiveness of ETR for the evaluation of performance of bearing degradation. To justify the preeminence of recommended approach, it is compared with the performance of random forest regression and multi-layer perceptron regression.
Originality/value
The experimental results indicated that the presently adopted method shows better performance for detecting the degradation more accurately at early stage. Furthermore, the diagnostics and prognostics have been getting much attention in the field of vibration, and it plays a significant role to avoid accidents.
Details
Keywords
Yong Liu, Jiang Zhang, Junjie Cui, Changsong Zheng, Yajun Liu and Jian Shen
In armored vehicles integrated transmissions, residual life prediction based on oil spectrum data is crucial for condition monitoring and reliability assessment. This paper aims…
Abstract
Purpose
In armored vehicles integrated transmissions, residual life prediction based on oil spectrum data is crucial for condition monitoring and reliability assessment. This paper aims to use the advantages of real-time and accurate prediction of binary Wiener process, the residual life prediction of clutch is studied.
Design/methodology/approach
First, combined with the wet clutch life test, the indicator elements Cu and Pb and the failure threshold of the residual life prediction of the clutch are extracted through the oil replacement correction of the spectral data of the whole life cycle; second, the correlation characteristics of indicating elements are analyzed by MATLAB Copula function, then the correlation function of residual life will be derived; third, according to the inverse Gaussian principle, the performance degradation mathematical models of the unary and binary Wiener processes of the above two indicator elements are established; finally, the maximum likelihood estimation method is used to estimate the parameters, and the monadic and binary performance degradation mathematical models are used to predict the residual life of the tested clutch.
Findings
By comparing the prediction results with the test results, with the passage of time, 81.25% of the predicted value error of the residual life prediction method based on the binary Wiener process is controlled within 20%, while 56.25% of the predicted value error of the residual life prediction method based on the unitary Wiener process is controlled within 20%. At the same time, the prediction accuracy of the binary prediction model is 2%–16.7% higher than that of the unitary prediction model.
Originality/value
This paper studies the residual life prediction theory of wet clutch, which can develop the theory and method of comprehensive transmission health monitoring, and provide theoretical and technical support for the construction of a reliable health management system for high-speed tracked vehicles.
Details